Computing platforms evolve over time. Originally computers were directed by hardware wiring - that, the “code” was the path of the wiring that directed an electrical signal from one component to another, or in some cases a physical switch controlled the path. From there software was developed, first in a very low machine language, then when compilers were created, computer languages could more closely mimic written statements. These language statements can be compiled into the lower-level machine language still used by computers today.

The reason this history is important is that along each technology advancement, computer code has adapted. Writing software for a RISC architecture is significantly different than developing for a CISC architecture. And moving to a Distributed Architecture like Windows Azure also has specific implementation details that our code must follow.

But why make a change? As I’ve described, we need to make the change to our code to follow advances in technology. There’s no point in change for its own sake, but as a new paradigm offers benefits to our users, it’s important for us to leverage those benefits where it makes sense.

That’s most often done in new development projects. It’s a far simpler task to take a new project and adapt it to Windows Azure than to try and retrofit older code designed in a previous computing environment. We can still use the same coding languages (.NET, Java, C++) to write code for Windows Azure, but we need to think about the architecture of that code on a new project so that it runs in the most efficient, cost-effective way in a Distributed Architecture.

As we receive new requests from the organization for new projects, a distributed architecture paradigm belongs in the decision matrix for the platform target.

Implementation:

When you are designing new applications for Windows Azure (or any distributed architecture) there are many important details to consider. But at the risk of over-simplification, there are three main concepts to learn and architect within the new code:

Stateless Programming - Stateless program is a prime concept within distributed architectures. Rather than each server owning the complete processing cycle, the information from an operation that needs to be retained (the “state”) should be persisted to another location c(like storage) common to all machines involved in the process. An interesting learning process for Stateless Programming (although not unique to this language type) is to learn Functional Programming.

Server-Side Processing - Along with developing using a Stateless Design, the closer you can locate the code processing to the data, the less expensive and faster the code will run. When you control the network layer, this is less important, since you can send vast amounts of data between the server and client, allowing the client to perform processing. In a distributed architecture, you don’t always own the network, so it’s performance is unpredictable. Also, you may not be able to control the platform the user is on (such as a smartphone, PC or tablet), so it’s imperative to deliver only results and graphical elements where possible.

Token-Based Authentication - Also called “Claims-Based Authorization”, this code practice means instead of allowing a user to log on once and then running code in that context, a more granular level of security is used. A “token” or “claim”, often represented as a Certificate, is sent along for a series or even one request. In other words, every call to the code is authenticated against the token, rather than allowing a user free reign within the code call. While this is more work initially, it can bring a greater level of security, and it is far more resilient to disconnections.